CN111243007A - Reliable parameter extraction method - Google Patents
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- CN111243007A CN111243007A CN201910255276.7A CN201910255276A CN111243007A CN 111243007 A CN111243007 A CN 111243007A CN 201910255276 A CN201910255276 A CN 201910255276A CN 111243007 A CN111243007 A CN 111243007A
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- 230000000007 visual effect Effects 0.000 claims abstract description 6
- 238000001914 filtration Methods 0.000 claims description 67
- 238000012545 processing Methods 0.000 claims description 53
- 238000000034 method Methods 0.000 claims description 16
- 238000003384 imaging method Methods 0.000 claims description 8
- 239000002893 slag Substances 0.000 claims description 8
- 239000002689 soil Substances 0.000 claims description 8
- 230000009471 action Effects 0.000 claims description 6
- 238000001514 detection method Methods 0.000 claims description 6
- 230000003044 adaptive effect Effects 0.000 claims description 4
- 230000006872 improvement Effects 0.000 claims description 3
- 238000009529 body temperature measurement Methods 0.000 claims description 2
- 238000013507 mapping Methods 0.000 claims description 2
- 239000010453 quartz Substances 0.000 claims description 2
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 claims description 2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
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Abstract
The invention relates to a reliable parameter extraction method which comprises the steps of using a reliable parameter extraction platform to judge the volume of muck exposed out of a muck truck by adopting a visual identification mechanism, and determining whether the corresponding muck truck is overloaded or not based on a judgment result, so that the situation of overload misjudgment is avoided.
Description
Technical Field
The invention relates to the field of building construction, in particular to a reliable parameter extraction method.
Background
Overload (Overload) refers to the actual load of a vehicle exceeding a certified maximum allowable limit, and freight Overload generally refers to the excess of cargo transported by a motor vehicle over the gross load of a freight motor vehicle.
The damage and loss caused by the overload transportation of the freight vehicle are surprised, and the related departments continuously emphasize and strictly manage, but the situation is not cured frequently, the overload condition is not radically improved at present, and some places are further cured, so that the situation becomes a cancer of road transportation. According to the investigation of relevant departments, the overload overrun proportion of various freight vehicles with the load of 2.5 tons is as high as 30 percent to 85 percent. The maximum loading rate of the overloaded vehicles is above 300 percent, and the maximum loading rate is 760 percent, namely the actual loading capacity of 1 truck with the rated load of 2 tons reaches 15 tons. According to the investigation of relevant departments in some important overload areas, the transport vehicles are almost overloaded by 100 percent, the overload degree is generally more than one time, and some overload degrees reach 5 to 6 times. Such overloading means that the road surface laid by the steel plate will also sink and break.
At present, muck trucks are often used at construction sites to transport the muck keeping the construction site clean. Once the muck truck is detected to be overloaded, the fine and treatment on the building side are irrevocable, the overload judgment of the muck truck is generally carried out by adopting a muck height judgment mechanism, and certain errors and limitations exist when the muck truck is judged to be overloaded or not based on the muck height.
Disclosure of Invention
The invention has at least the following three important points:
(1) because the judgment of whether the muck truck is overloaded or not has certain errors and limitations based on the muck height, a visual identification mechanism is adopted to carry out numerical judgment on the volume of the muck exposed out of the muck truck, and whether the corresponding muck truck is overloaded or not is determined based on the judgment result, so that the overload misjudgment is avoided;
(2) acquiring each red channel value of each pixel point in an image, and calculating the mean square error of each red channel value to serve as a target mean square error so as to provide important reference data for judging the complexity of the image content;
(3) on the basis of the midpoint filtering, the targeted image processing is performed on different color components in the CMYK color space to reduce the data amount of the image processing and improve the targeting of the image processing.
According to one aspect of the invention, a reliable parameter extraction method is provided, the method includes using a reliable parameter extraction platform to perform numerical judgment on the volume of the muck exposed out of the muck truck by adopting a visual identification mechanism, and determining whether the corresponding muck truck is overloaded based on a judgment result, so as to avoid the occurrence of overload misjudgment, and the reliable parameter extraction platform includes:
the self-adaptive analysis equipment is connected with the harmonic mean filtering equipment and is used for analyzing the muck object in the re-filtered image when the matching degree of the re-filtered image and the preset muck vehicle shape exceeds the limit so as to obtain the depth of field of the muck object and the imaging area where the muck object is located;
the overload judgment device is connected with the self-adaptive analysis device and used for determining the predicted volume of the muck object as the exposed muck volume based on the depth of field of the muck object and the area proportion of the imaging area where the muck object is located occupying the re-filtered image, and sending an overload identification signal when the exposed muck volume is larger than or equal to a preset volume threshold value, or sending an overload unidentified signal;
the weight detection equipment is buried below the land in front of the earth moving channel and used for sending a first control command when detecting that the weight exceeds the limit, and otherwise, sending a second control command;
the embedded camera is arranged in front of the earth moving channel, connected with the weight detection equipment and used for starting the camera shooting action of the earth moving scene in the earth moving channel when receiving a first control command so as to obtain a corresponding earth moving scene image;
the embedded camera is also used for stopping the shooting action of the earth moving scene in the earth moving channel when receiving a second control command;
the parameter extraction equipment is connected with the embedded camera and used for receiving the earth-moving scene image, acquiring each red channel value of each pixel point in the earth-moving scene image, and calculating the mean square error of each red channel value to be used as a target mean square error to be output;
the content judgment device is connected with the parameter extraction device and used for receiving the target mean square error, determining the content complexity of the corresponding earth-moving scene image based on the numerical distribution range of the target mean square error and outputting the content complexity as the target complexity;
the parameter extraction equipment and the content judgment equipment are respectively realized by adopting SOC chips with different models and share the same clock oscillator;
the midpoint filtering device is used for receiving the earth-moving scene image, executing midpoint filtering processing on the earth-moving scene image to obtain a corresponding midpoint filtering image, and restoring power connection when the received target complexity exceeds a preset complexity threshold value, or cutting off power connection;
the first processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and executing edge enhancement processing on a cyan component sub-image formed by cyan components of each pixel point in the midpoint filtering image to obtain a first processed image;
the second processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and carrying out sharpening processing on a magenta component sub-image formed by the magenta components of each pixel point in the midpoint filtering image so as to obtain a second processed image;
the third processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and executing contrast improvement processing on a yellow component sub-image formed by yellow components of each pixel point in the midpoint filtering image so as to obtain a third processed image;
the fourth processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and executing enhancement processing on a black component sub-image formed by black components of each pixel point in the midpoint filtering image so as to obtain a fourth processed image;
and the harmonic mean filtering equipment is respectively connected with the first processing equipment, the second processing equipment, the third processing equipment and the fourth processing equipment and is used for executing harmonic mean filtering processing on the image obtained by superposing the first processed image, the second processed image, the third processed image and the fourth processed image so as to obtain a corresponding re-filtered image.
The reliable parameter extraction platform is convenient to use and reliable in data. Because the judgment of whether the muck truck is overloaded or not based on the muck height has certain errors and limitations, a visual identification mechanism is adopted to carry out numerical judgment on the volume of the muck exposed out of the muck truck, and whether the corresponding muck truck is overloaded or not is determined based on the judgment result, so that the overload misjudgment is avoided.
Detailed Description
Embodiments of the present invention will be described in detail below.
In order to overcome the defects, the invention provides a reliable parameter extraction method which comprises the steps of using a reliable parameter extraction platform to judge the volume of the muck exposed out of the muck car by adopting a visual identification mechanism, and determining whether the corresponding muck car is overloaded or not based on a judgment result, so that the situation of overload misjudgment is avoided, and the reliable parameter extraction platform can effectively solve the corresponding technical problem.
The reliable parameter extraction platform shown according to the embodiment of the invention comprises:
the self-adaptive analysis equipment is connected with the harmonic mean filtering equipment and is used for analyzing the muck object in the re-filtered image when the matching degree of the re-filtered image and the preset muck vehicle shape exceeds the limit so as to obtain the depth of field of the muck object and the imaging area where the muck object is located;
the overload judgment device is connected with the self-adaptive analysis device and used for determining the predicted volume of the muck object as the exposed muck volume based on the depth of field of the muck object and the area proportion of the imaging area where the muck object is located occupying the re-filtered image, and sending an overload identification signal when the exposed muck volume is larger than or equal to a preset volume threshold value, or sending an overload unidentified signal;
the weight detection equipment is buried below the land in front of the earth moving channel and used for sending a first control command when detecting that the weight exceeds the limit, and otherwise, sending a second control command;
the embedded camera is arranged in front of the earth moving channel, connected with the weight detection equipment and used for starting the camera shooting action of the earth moving scene in the earth moving channel when receiving a first control command so as to obtain a corresponding earth moving scene image;
the embedded camera is also used for stopping the shooting action of the earth moving scene in the earth moving channel when receiving a second control command;
the parameter extraction equipment is connected with the embedded camera and used for receiving the earth-moving scene image, acquiring each red channel value of each pixel point in the earth-moving scene image, and calculating the mean square error of each red channel value to be used as a target mean square error to be output;
the content judgment device is connected with the parameter extraction device and used for receiving the target mean square error, determining the content complexity of the corresponding earth-moving scene image based on the numerical distribution range of the target mean square error and outputting the content complexity as the target complexity;
the parameter extraction equipment and the content judgment equipment are respectively realized by adopting SOC chips with different models and share the same clock oscillator;
the midpoint filtering device is used for receiving the earth-moving scene image, executing midpoint filtering processing on the earth-moving scene image to obtain a corresponding midpoint filtering image, and restoring power connection when the received target complexity exceeds a preset complexity threshold value, or cutting off power connection;
the first processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and executing edge enhancement processing on a cyan component sub-image formed by cyan components of each pixel point in the midpoint filtering image to obtain a first processed image;
the second processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and carrying out sharpening processing on a magenta component sub-image formed by the magenta components of each pixel point in the midpoint filtering image so as to obtain a second processed image;
the third processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and executing contrast improvement processing on a yellow component sub-image formed by yellow components of each pixel point in the midpoint filtering image so as to obtain a third processed image;
the fourth processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and executing enhancement processing on a black component sub-image formed by black components of each pixel point in the midpoint filtering image so as to obtain a fourth processed image;
harmonic mean filtering equipment which is respectively connected with the first processing equipment, the second processing equipment, the third processing equipment and the fourth processing equipment and is used for performing harmonic mean filtering processing on the images obtained by superposing the first processed image, the second processed image, the third processed image and the fourth processed image so as to obtain corresponding re-filtered images;
wherein, in the adaptive analysis device, analyzing the muck object in the re-filtered image comprises: taking the pixel points with the gray values within the preset slag soil gray scale range as slag soil pixel points;
and the self-adaptive analysis equipment is also used for fitting an imaging area where the slag soil object is located based on each slag soil pixel point in the re-filtered image.
Next, a detailed structure of the reliable parameter extraction platform of the present invention will be further described.
In the reliable parameter extraction platform:
the harmonic mean filtering device, the adaptive analysis device and the overload judgment device are all realized by adopting programmable logic devices.
In the reliable parameter extraction platform:
the first processing device, the second processing device, the third processing device and the fourth processing device share the same quartz oscillator.
In the reliable parameter extraction platform, the method further comprises:
and the data switching equipment is respectively connected with the DRAM memory chip, the harmonic mean filtering equipment and the temperature analysis equipment, and the harmonic mean filtering equipment is arranged near the self-adaptive analysis equipment and is connected with the self-adaptive analysis equipment.
In the reliable parameter extraction platform, the method further comprises:
and the DRAM memory chip is connected with the data switching equipment and is used for storing the mapping relation between the surface temperature and the complexity of the received data.
In the reliable parameter extraction platform, the method further comprises:
and the surface temperature measuring equipment is arranged on the surface of the self-adaptive analysis equipment and used for detecting the surface temperature of the self-adaptive analysis equipment to be output as the surface temperature of the equipment.
In the reliable parameter extraction platform, the method further comprises:
and the temperature analysis equipment is connected with the surface temperature measurement equipment, is used for receiving the surface temperature of the equipment, and sends out a temperature standard exceeding instruction when the received surface temperature of the equipment is greater than or equal to a preset temperature threshold value, and is also used for sending out a temperature standard combining instruction when the surface temperature of the equipment is less than the preset temperature threshold value.
In the reliable parameter extraction platform:
and the data switching equipment is used for switching the complexity of the received data of the harmonic mean filtering equipment based on the numerical value of the equipment surface temperature when the temperature standard exceeding instruction is received.
In the reliable parameter extraction platform:
the data switching device is further configured to maintain the complexity of the received data of the harmonic mean filtering device when the temperature scaling command is received.
In the reliable parameter extraction platform:
in the data switching device, switching the complexity of the received data of the harmonic mean filtering device based on the value of the device surface temperature includes: the complexity of the received data of the switched harmonic mean filter device is inversely proportional to the value of the surface temperature of the device.
In addition, dram (dynamic Random Access memory), which is a dynamic Random Access memory, is the most common system memory. DRAM can hold data only for a short time. To retain data, DRAM uses capacitive storage, so must be refreshed (refresh) once at intervals, and if the memory cells are not refreshed, the stored information is lost. (shutdown will lose data). Dynamic RAM is also comprised of a number of basic memory cells multiplexed by row and column address pins.
The structure of the DRAM is simple and efficient, and each bit only needs one transistor and one capacitor. However, the capacitance inevitably has leakage phenomenon, which causes data error if the charge is insufficient, and therefore, the capacitance must be periodically refreshed (precharged), which is also a big feature of the DRAM. Moreover, the charging and discharging of the capacitor requires a process, and the refresh frequency cannot be raised infinitely (frequency barrier), which results in that the frequency of the DRAM can easily reach the upper limit, and even if the advanced process is supported, the effect is very small. With the advancement of technology and the desire of people to overclock, these frequency barriers are being solved slowly.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (10)
1. A reliable parameter extraction method comprises the steps of using a reliable parameter extraction platform to carry out numerical judgment on the volume of muck exposed out of a muck truck by adopting a visual identification mechanism, and determining whether the corresponding muck truck is overloaded or not based on a judgment result so as to avoid the occurrence of overload misjudgment, wherein the reliable parameter extraction platform comprises the following steps:
the self-adaptive analysis equipment is connected with the harmonic mean filtering equipment and is used for analyzing the muck object in the re-filtered image when the matching degree of the re-filtered image and the preset muck vehicle shape exceeds the limit so as to obtain the depth of field of the muck object and the imaging area where the muck object is located;
the overload judgment device is connected with the self-adaptive analysis device and used for determining the predicted volume of the muck object as the exposed muck volume based on the depth of field of the muck object and the area proportion of the imaging area where the muck object is located occupying the re-filtered image, and sending an overload identification signal when the exposed muck volume is larger than or equal to a preset volume threshold value, or sending an overload unidentified signal;
the weight detection equipment is buried below the land in front of the earth moving channel and used for sending a first control command when detecting that the weight exceeds the limit, and otherwise, sending a second control command;
the embedded camera is arranged in front of the earth moving channel, connected with the weight detection equipment and used for starting the camera shooting action of the earth moving scene in the earth moving channel when receiving a first control command so as to obtain a corresponding earth moving scene image;
the embedded camera is also used for stopping the shooting action of the earth moving scene in the earth moving channel when receiving a second control command;
the parameter extraction equipment is connected with the embedded camera and used for receiving the earth-moving scene image, acquiring each red channel value of each pixel point in the earth-moving scene image, and calculating the mean square error of each red channel value to be used as a target mean square error to be output;
the content judgment device is connected with the parameter extraction device and used for receiving the target mean square error, determining the content complexity of the corresponding earth-moving scene image based on the numerical distribution range of the target mean square error and outputting the content complexity as the target complexity;
the parameter extraction equipment and the content judgment equipment are respectively realized by adopting SOC chips with different models and share the same clock oscillator;
the midpoint filtering device is used for receiving the earth-moving scene image, executing midpoint filtering processing on the earth-moving scene image to obtain a corresponding midpoint filtering image, and restoring power connection when the received target complexity exceeds a preset complexity threshold value, or cutting off power connection;
the first processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and executing edge enhancement processing on a cyan component sub-image formed by cyan components of each pixel point in the midpoint filtering image to obtain a first processed image;
the second processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and carrying out sharpening processing on a magenta component sub-image formed by the magenta components of each pixel point in the midpoint filtering image so as to obtain a second processed image;
the third processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and executing contrast improvement processing on a yellow component sub-image formed by yellow components of each pixel point in the midpoint filtering image so as to obtain a third processed image;
the fourth processing device is connected with the midpoint filtering device and used for receiving the midpoint filtering image and executing enhancement processing on a black component sub-image formed by black components of each pixel point in the midpoint filtering image so as to obtain a fourth processed image;
harmonic mean filtering equipment which is respectively connected with the first processing equipment, the second processing equipment, the third processing equipment and the fourth processing equipment and is used for performing harmonic mean filtering processing on the images obtained by superposing the first processed image, the second processed image, the third processed image and the fourth processed image so as to obtain corresponding re-filtered images;
wherein, in the adaptive analysis device, analyzing the muck object in the re-filtered image comprises: taking the pixel points with the gray values within the preset slag soil gray scale range as slag soil pixel points;
and the self-adaptive analysis equipment is also used for fitting an imaging area where the slag soil object is located based on each slag soil pixel point in the re-filtered image.
2. The method of claim 1, wherein:
the harmonic mean filtering device, the adaptive analysis device and the overload judgment device are all realized by adopting programmable logic devices.
3. The method of claim 2, wherein:
the first processing device, the second processing device, the third processing device and the fourth processing device share the same quartz oscillator.
4. The method of claim 3, wherein the platform further comprises:
and the data switching equipment is respectively connected with the DRAM memory chip, the harmonic mean filtering equipment and the temperature analysis equipment, and the harmonic mean filtering equipment is arranged near the self-adaptive analysis equipment and is connected with the self-adaptive analysis equipment.
5. The method of claim 4, wherein the platform further comprises:
and the DRAM memory chip is connected with the data switching equipment and is used for storing the mapping relation between the surface temperature and the complexity of the received data.
6. The method of claim 5, wherein the platform further comprises:
and the surface temperature measuring equipment is arranged on the surface of the self-adaptive analysis equipment and used for detecting the surface temperature of the self-adaptive analysis equipment to be output as the surface temperature of the equipment.
7. The method of claim 6, wherein the platform further comprises:
and the temperature analysis equipment is connected with the surface temperature measurement equipment, is used for receiving the surface temperature of the equipment, and sends out a temperature standard exceeding instruction when the received surface temperature of the equipment is greater than or equal to a preset temperature threshold value, and is also used for sending out a temperature standard combining instruction when the surface temperature of the equipment is less than the preset temperature threshold value.
8. The method of claim 7, wherein:
and the data switching equipment is used for switching the complexity of the received data of the harmonic mean filtering equipment based on the numerical value of the equipment surface temperature when the temperature standard exceeding instruction is received.
9. The method of claim 8, wherein:
the data switching device is further configured to maintain the complexity of the received data of the harmonic mean filtering device when the temperature scaling command is received.
10. The method of any of claims 1-9, wherein:
in the data switching device, switching the complexity of the received data of the harmonic mean filtering device based on the value of the device surface temperature includes: the complexity of the received data of the switched harmonic mean filter device is inversely proportional to the value of the surface temperature of the device.
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| CN113066045A (en) * | 2020-10-18 | 2021-07-02 | 无锡臻永科技有限公司 | Transmission performance analysis system |
| CN114005092A (en) * | 2021-12-29 | 2022-02-01 | 深圳市思拓通信系统有限公司 | Muck truck bearing capacity monitoring method, controller and system |
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